Research On Spectrum Detection Algorithm Of Cognitive Radio System

Cognitive radio (CR) technology can get the available spectrum resources (Spectrum holes) through spectrum detection, and distribute these Spectrum holes again to supply unauthorized users. This dynamic spectrum allocation method is a potential solution for contradiction between spectrum shortage and the low utilization rate. It has become a hot spot of the future wireless communication field, the spectrum detection technology is one of the key technologies for cognitive radio.The thesis analyzes the concept of Cognitive Radio teehnology, the study status quo at home and abroad, and the spectrum detection teehnologies which are usually used, and focus on the prineiples and performance of energy detection and cooperation spectrum detection, laying a theoretical foundation for research.In traditional cooperation spectrum detection, the reliability of the secondary users (SU) nodes has been ignored, the access point treat these detection results by SU equally, which makes the system performance is very vulnerable to a malicious user interference. Based on analysis of the problem, this paper introduces a novel cooperative spectrum detection method, considering the effect of distance fading on different second users and the credibility of spectrum detection from each second user. Furthermore, this paper discusses the relationship between the credibility and the distance. The simulation results show that the performance of the algorithm is better than traditional multi-node detection, which improve the reliability of spectrum detection in cognitive radio system.Traditional energy detection algorithm is improved in the paper, we get the new detection model by setting multiple thresholds in uncertainty detection area. Proposing a new cooperative spectrum detection algorithm combined with multi-threshold energy detection. We do futher processing for the detection results, which fall in the uncertainty detection area, local detection result can be obtained by judging cognitive user node's detection statistics. And center detection node makes final decision using various local detection results. Furthermore, this paper discusses the relationship between the detection performance and the size of the uncertainty detection area. Simulation results show that the algorithm proposed in this paper has certain advantages in the frequency spectrum detection performance compared with traditional cooperation frequency detection algorithm.